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Refractoriness to induction therapy and relapse after complete remission are the leading causes of death in patients with acute myeloid leukaemia (AML). This study focussed on the prediction of response to standard induction therapy and outcome of patients with AML using a combined strategy of mutational profiling by next-generation sequencing (NGS, n = 190) and ex vivo PharmaFlow testing (n = 74) for the 10 most widely used drugs for AML induction therapy, in a cohort of adult patients uniformly treated according to Spanish PETHEMA guidelines. We identified an adverse mutational profile (EZH2, KMT2A, U2AF1 and/or TP53 mutations) that carries a greater risk of death [hazard ratio (HR): 3·29, P < 0·0001]. A high correlation was found between the ex vivo PharmaFlow results and clinical induction response (69%). Clinical correlation analysis showed that the pattern of multiresistance revealed by ex vivo PharmaFlow identified patients with a high risk of death (HR: 2·58). Patients with mutation status also ran a high risk (HR 4·19), and the risk was increased further in patients with both adverse profiles (HR 4·82). We have developed a new score based on NGS and ex vivo drug testing for AML patients that improves upon current prognostic risk stratification and allows clinicians to tailor treatments to minimise drug resistance., (© 2020 British Society for Haematology and John Wiley & Sons Ltd.)

Complete remission (CR) after induction therapy is the first treatment goal in acute myeloid leukemia (AML) patients and has prognostic impact. Our purpose is to determine the correlation between the observed CR/CRi rate after idarubicin (IDA) and cytarabine (CYT) 3 + 7 induction and the leukemic chemosensitivity measured by an ex vivo test of drug activity. Bone marrow samples from adult patients with newly diagnosed AML were included in this study. Whole bone marrow samples were incubated for 48 h in well plates containing IDA, CYT, or their combination. Pharmacological response parameters were estimated using population pharmacodynamic models. Patients attaining a CR/CRi with up to two induction cycles of 3 + 7 were classified as responders and the remaining as resistant. A total of 123 patients fulfilled the inclusion criteria and were evaluable for correlation analyses. The strongest clinical predictors were the area under the curve of the concentration response curves of CYT and IDA. The overall accuracy achieved using MaxSpSe criteria to define positivity was 81%, predicting better responder (93%) than non-responder patients (60%). The ex vivo test provides better yet similar information than cytogenetics, but can be provided before treatment representing a valuable in-time addition. After validation in an external cohort, this novel ex vivo test could be useful to select AML patients for 3 + 7 regimen vs. alternative schedules., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: We have evaluated the ex vivo pharmacology of single drugs and drug combinations in malignant cells of bone marrow samples from 125 patients with acute myeloid leukemia using a novel automated flow cytometry-based platform (ExviTech). We have improved previous ex vivo drug testing with 4 innovations: identifying individual leukemic cells, using intact whole blood during the incubation, using an automated platform that escalates reliably data, and performing analyses pharmacodynamic population models., Patients and Methods: Samples were sent from 24 hospitals to a central laboratory and incubated for 48 hours in whole blood, after which drug activity was measured in terms of depletion of leukemic cells., Results: The sensitivity of single drugs is assessed for standard efficacy (EMAX) and potency (EC50) variables, ranked as percentiles within the population. The sensitivity of drug-combination treatments is assessed for the synergism achieved in each patient sample. We found a large variability among patient samples in the dose-response curves to a single drug or combination treatment., Conclusion: We hypothesize that the use of the individual patient ex vivo pharmacological profiles may help to guide a personalized treatment selection., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)